code: def forward(
      self,
      batch_idx: int,
      batch: tensor_dict_type,
      state: Optional["TrainerState"] = None,
      **kwargs: Any,
  ) -> tensor_dict_type:
      results = super().forward(batch_idx, batch, state, **kwargs)
      results[LATENT_KEY] = l2_normalize(results["pooler_output"])
      return results
  
file_path: carefree-learn/cflearn/models/nlp/transformers/simbert.py
imports: from typing import Any
  from typing import Optional
  from cftool.array import l2_normalize
  from cftool.types import tensor_dict_type
  from .core import HuggingFaceModel
  from ....schema import TrainerState
  from ....constants import LATENT_KEY
label_desc: Use image node_id 2 for calling the SimBERT obj's underlying member method code with example usage: obj.forward(batch_idx, batch, state) and returns: results